say my column is something like this:
trade_signal buy buy buy buy sell sell sell sell buy buy buy sell sell buy sell buy
I would like to drop the duplicate elements in the column and replace them with NAN or 0 so it would end up with something like:
trade_signal buy nan nan nan sell nan nan nan buy nan nan sell nan buy sell buy
I am completely unsure of the logic I can use to do this, I think I would forward fill up until the next change in signal with NAN values somehow?
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Answer
Try mask with shift:
df['trade_signal'] = df['trade_signal'].mask(df['trade_signal'].eq(
df['trade_signal'].shift())
)
trade_signal 0 buy 1 NaN 2 NaN 3 NaN 4 sell 5 NaN 6 NaN 7 NaN 8 buy 9 NaN 10 NaN 11 sell 12 NaN 13 buy 14 sell 15 buy